176 to 200 of 2,936 Machine Learning Jobs in London

and deep learning, acting as a critical bridge between theory and implementation: designing, building, and scaling the complex systems on which our ML research depends. You'll be joining a team with access to cutting-edge multiomic and interventional datasets, advanced computational infrastructure, and deep interdisciplinary expertise … culture that embraces modern ML tooling, including agentic workflows. Key responsibilities include implementing and optimising large neural network models; building robust infrastructure for distributed training, evaluation, and inference; and partnering with ML Scientists to take research from prototype to production-grade systems applied to large, multi-modal biological data, tested ...

complex physical system. Data Centers are the proof point, not the ceiling. We have sites in London, Canada and the USA, building teams across ML research, Product development, Mechanical engineering, and Chemical engineering. If you want to work where AI meets atoms, we'd like to hear from you. … technology challenges. Key Responsibilities Set the technical bar and ensure engineering excellence Establish and maintain exceptionally high standards for code quality, system architecture and ML research and engineering practices through hands‐on coding and technical review Design robust, well‐engineered systems that others can build upon, balancing research velocity with ...

large AI models, reinforcement learning, synthetic data and multi-agent systems. You'll combine hands‐on engineering with research, building and experimenting with ML systems, developing robust research infrastructure and working alongside researchers on complex, rapidly evolving problems. Non negotiable skills: 2+ years' hands-on Machine Learning/AI experience - including ML, artificial intelligence, recommendation systems or pattern recognition. Strong Python programming skills Experience developing ML models at scale Experience running complex experiments with large AI models and datasets. Strong understanding of the scientific/research process and the ability to investigate why approaches succeed ...

digital landscape. As an Associate Director Data Scientist in our growing Data & AI team, you’ll lead the design and delivery of advanced analytics, machine learning and Generative AI solutions, turning complex business and tax challenges into scalable, production-ready products and services. The role combines hands … into practical business solutions. Experience shaping Data & AI strategy, roadmaps and technical standards. Experience building reusable AI assets, frameworks or products. Strong understanding of ML/LLMOps, CI/CD, model monitoring and production deployment. Experience with agentic AI, RAG and knowledge-based systems. Experience operating within regulated or risk ...

exploratory research into AI methods and approaches, bespoke solutions to complex customer problems, and infrastructure projects working across large customer datasets. As a Senior ML Engineer, you will design, develop, and iterate on machine learning models that support national security objectives. You will collaborate with Data Scientists, Software … experiments, track results, and deliver scalable solutions. A key aspect to the role is to balance rapid experimentation with production readiness, prototyping and validating ML approaches while ensuring successful experiments integrate seamlessly into operational systems. This is an exciting time to join our team to help pioneer both our customer ...

Excellent problem‐solving skills and the ability to work independently and as part of a team. Strong programming skills in Python and experience with ML libraries such as PyTorch or vLLM. Working towards or holding a Masters or PhD in NLP or a related quantitative field (machine learning, computer science, mathematics, statistics, physics or engineering). Publications at leading NLP conferences (ACL, EMNLP) and ML conferences (NeurIPS, ICML) are highly desirable. Interest in applying NLP concepts to real‐world financial data and implementing theoretical insights as working code. Strong communication skills, both written and verbal ...

defining best practices. Working with clients, and cross-functional teams, you'll ensure technical feasibility and timely delivery of high-quality, production-grade ML systems. What you'll be doing: Building and deploying production-grade ML software, tools, and infrastructure. Creating reusable, scalable solutions that accelerate the delivery of ML … implementing Faculty’s standards for deploying machine learning at scale. Acting as a technical advisor to customers and partners, translating complex ML concepts for stakeholders. Who we're looking for: You understand the full machine learning lifecycle and have experience operationalising models built with frameworks like ...

Longshot Systems we build advanced platforms for sports betting analytics and trading. We're hiring Machine Learning Engineers across our core ML engineering and horse racing teams. You'd be designing, building and productionising ML pipelines, tooling, visualisation, frameworks and data engineering workflows to support strategy research, analysis … latency components forward. The ideal candidate will have a strong software engineering background with a track record of building and maintaining production-grade ML pipelines. We are looking for engineers who are comfortable designing robust data engineering workflows, building reliable tooling, and writing clean, maintainable Python code alongside high-performance ...

predictive methods to client data about their customer behavior particularly in relation to marketing, website interactions and online conversions. We primarily use Python, classical ML techniques, and rapid iteration leveraging AI. Our methods require custom adaptations in terms of methods, features, optimization methods, and ML algorithm selection, as well … science expertise and work on a variety of genuinely interesting client projects. Key responsibilities include, but are not limited to: Manage data science and ML projects so that technical goals are met within a reasonable agreed timeframe. Communicate clearly about your work with clients and to help other team members ...

where integrity guides decisions, **relentless service** sets the bar, and we **thrive on big challenges** together. We invest in your growth with enterprise‐wide learning and mobility. We celebrate who you are, and we respect life beyond work with flexibility that’s recognized externally. Enabled by modern platforms … scale.**Job Description:**## Advanced Technologies Consultant### Position SummaryThe Advanced Technologies Consultant supports clients in the effective, defensible, and commercially practical use of analytics, machine learning, and generative AI across eDiscovery, document review, investigations, early case assessment, privilege review, regulatory response, and related legal data workflows.Working closely with ...

technology challenges. Key Responsibilities Set the technical bar and ensure engineering excellence Establish and maintain exceptionally high standards for code quality, system architecture and ML research and engineering practices through hands-on coding and technical review Design robust, well-engineered systems that others can build upon, balancing research velocity with … development, contributing significantly to the codebase Balance research rigour with pragmatic engineering to deliver production-ready systems at scale Push the frontier of ML research Design and implement novel ML architectures for complex scientific domains, with work that meets publication standards at top-tier conferences Drive research projects from conception ...

/ML Postdoctoral Fellow – F Rouhani Lab Contract term: This is a full-time, fixed term (4 years) position on Crick terms and conditions of employment. Reports to: Foad Rouhani, Group Leader Salary for this Role: From £47,500 with benefits, subject to skills and experience About us The Francis … harnessed to develop future therapies. Using the liver as a model system, the lab combines stem cell biology, spatial genomics, AI/ML, single-cell technologies and computational biology to study how mutant cell populations interact with their surrounding tissue environment during regeneration, ageing and cancer development. About the role ...

evaluate new internal software releases, provide feedback to software engineering teams, make necessary code fixes, and conduct code reviews. Benchmark models and key ML techniques to identify performance bottlenecks and improve model efficiency. Design and conduct experiments on novel AI methods, implement them and evaluate results. Collaborate with Research, Software … C++ software development skills. Expertise in deep learning from model training to optimisation and evaluation. Experience in distributed training or inference of ML models across 64+ accelerators. Capable of designing, executing and reporting from ML experiments. Developed deep understanding of performance bottlenecks and how to overcome them. Ability ...

offer a competitive salary, a great location, and a supportive, people-first culture where your growth truly matters. With access to global projects, learning opportunities, and an inclusive environment that values every voice, you’ll have the space to shape the future with us. About The Team … implement, and optimize AI agents for various applications, including customer service, supply chain optimization, recommendation systems, and internal operations. Develop robust agent architectures, incorporating machine learning models, natural language processing (NLP), knowledge representation, and reasoning techniques. Integrate AI agents with existing JD.com systems and platforms, ensuring seamless functionality ...

ML (Machine Learning) Engineer at Checkout.com in the Disputes ML team, you will contribute to the development of our brand‐new ML‐driven dispute optimisation suite. This is a unique opportunity to get in on the ground floor of an expanding area, grow alongside top‐tier engineers … dispute systems. Collaborate with platform and backend engineers to integrate models seamlessly. Experience and qualifications 5+ years of experience as an MLOps/ML Engineer. High proficiency in writing clear, production‐ready Python code. Experience with production ML models (online or offline) and standard MLOps practices. Experience with monitoring ...

communities in which we work and live. It is personal to all of us." – Julie Sweet, Accenture CEO. YOU ARE As an AI/ML Computational Scientist, you will design, build, and operationalize artificial intelligence and machine learning solutions for enterprise clients, combining custom models with cloud … include big data, high-performance compute, engineering simulations, scientific compute, grid and cloud computing, distributed networks Some experience in building and deploying AI/ML based software to a cloud environment. PREFERRED QUALIFICATION Proficiency in Python and python-based AI/ML framework and familiarity with relevant libraries and frameworks ...

Salary for this Role: From £47,500, with benefits, subject to skills and experience Job Title: AI/ML Postdoctoral Fellow – F Rouhani lab Reports to: Foad Rouhani [C] Closing Date: 23.59 GMT Job Description: AI/ML Postdoctoral Fellow – F Rouhani Lab Contract term: This is a full-time … harnessed to develop future therapies. Using the liver as a model system, the lab combines stem cell biology, spatial genomics, AI/ML, single-cell technologies and computational biology to study how mutant cell populations interact with their surrounding tissue environment during regeneration, ageing and cancer development. About the role ...

title: Machine Learning Engineer - Lumen Enterprise Models (SWE-focused LLMs) Location: London; full in-office working as default Start date: ASAP Reports to: CEO Compensation: Salary and Equity options available for discussion Application deadline: 08/11/26 at 23:59 UK time ___________________________________________________________________________ Help train the software … regressions. Collaborate with infrastructure, platform and data teams. ___________________________________________________________________________ What we’re looking for You may come from machine learning research, applied ML, model training or a closely related engineering background. You should have: Strong experience training deep-learning models in a production or research environment. Deep practical ...

/ML Engineer Up to £82,000 + Bonus + Outstanding Benefits + London/Hybrid If you're an AI Engineer who wants to build production AI solutions rather than endless proof of concepts, this is an opportunity to help shape how enterprise AI is adopted across a global …/LLMOps including deployment, monitoring, governance and lifecycle management. RAG, vector databases, prompt engineering and tool‐calling patterns. Building end-to-end AI/ML pipelines from data preparation through to production. Working with technical and business stakeholders to deliver AI solutions. Desirable experience includes MLflow, MCP, Docker, Kubernetes, GitLab ...

that ensure content remains safe, compliant, and high quality. We’re seeking a Senior Staff Machine Learning Engineer to build and scale ML systems that power safety, policy enforcement, and compliance across Spotify. In this role, you’ll shape how automated systems evaluate and act on content—ensuring … listeners and creators. What You Will Do Define & drive machine learning strategy for safety, policy enforcement, and compliance systems Build and scale ML systems for detection, classification, and risk assessment across content Develop automated decisioning systems that ensure consistent, reliable enforcement of policies Design systems that support real ...

development and unlocks the full potential of AI for professional engineers. We’re a compact, talent-dense technical team, with deep domain expertise in machine learning, formal verification and mathematical models of program semantics. Join us to develop the next frontier of formal reasoning and software engineering. Proof … degrees of predictability. Our roles require adaptability but, in return, we adapt to the candidate’s strengths. The entry point is depth in either machine learning or formal methods, alongside a strong software engineering background. We’re looking for Domain expertise in either machine learning ...

capabilities to support accurate, secure andpersonalised AI interactions. Design, build and maintainscalable machine learning training and inference pipelines usingDatabricks. Develop and productionisepredictive ML models for propensity scoring, next-best-actionrecommendations, churn prediction and cross-selling opportunities. Implement batch and real-timeinference solutions, optimising performance, latency and modelexplainability. Build … production AI development . Proficiency in Python andexperience developing, deploying and maintaining machine learning modelsin production. Experience building andmanaging end-to-end ML pipelines, including feature engineering, modeltraining, deployment and monitoring. Practical experience with Generative AI, Large LanguageModels (LLMs), RAG and AI agent architectures . Experience working withDatabricks ...

assumptions that need to hold, the confounders that need to be controlled for, and the experimental conditions that will make results actionable. AI/ML is the tool you bring to take those frameworks to a level of rigor, scale, and speed that wouldn't otherwise be possible - whether that … means building production-grade causal inference pipelines, designing ML-powered experiment analysis, or applying LLMs to accelerate how insights are generated and communicated. Responsibilities Design and implement marketing mix models and causal inference pipelines that quantify marketing effectiveness and inform budget allocation decisions Build and execute incrementality tests and translate ...

immediate interactions Partner with product managers, data scientists, and engineers to define what success looks like and how to measure it Own the full ML lifecycle, from data and modeling to deployment, monitoring, and iteration Integrate ML models with upstream systems, including domain value signals and opportunity generation frameworks Help … have strong experience building and deploying machine learning models in production environments at scale You are comfortable translating business problems into ML solutions and discussing trade‐offs with cross‐functional partners You have worked on complex optimization problems such as ranking systems or multi‐objective decision‐making ...

hiring an ML Ops Engineer to build and operate the platform capabilities that take machine-learning models from experimentation into reliable production services You’ll own the automation, deployment, observability and operational controls around the ML lifecycle, working closely with research engineers, software engineers, platform teams and product … teams This is not a research role. It is a hands-on engineering role focused on making ML systems reproducible, scalable, secure and dependable, from model packaging and release through to serving, monitoring, retraining and incident response ML lifecycle and platform engineering Build repeatable workflows for model training, validation, promotion ...